PPT-Priority Queues and Heaps

Lecture 19 CS2110 Spring 2014 1 Readings and Homework Read Chapter 26 to learn about heaps Salespeople often make matrices that show all the great features of their product that the competitors product lacks Try this for a heap versus a BST First try and sell . Data . Structures. Self-Adjusting. Data . Structures. 2. Lists. [D.D. . Sleator. , R.E. . Tarjan. , . Amortized Efficiency of List Update Rules. , Proc. 16. th. Annual ACM Symposium on Theory of Computing, 488-492, 1984]. COL 106. Shweta Agrawal and . Amit. Kumar. 2. Revisiting FindMin. Application: Find the smallest ( or highest priority) item quickly. Operating system. needs to schedule jobs according to priority instead of FIFO. Data . Structures. Self-Adjusting. Data . Structures. 2. Lists. [D.D. . Sleator. , R.E. . Tarjan. , . Amortized Efficiency of List Update Rules. , Proc. 16. th. Annual ACM Symposium on Theory of Computing, 488-492, 1984]. Lecture 16. CS2110 Spring 2015. Readings and Homework. Read Chapter 26. “A Heap Implementation” to learn about heaps. Exercise: . Salespeople often make matrices that show all the great features of their product that the competitor’s product lacks. Try this for a heap versus a BST. First, try and . A heap is a binary tree.. A heap is best implemented in sequential representation (using an array).. Two important uses of heaps are: . (. i. ) efficient implementation of priority queues. (ii) sorting -- . Lecture 16. CS2110 Fall 2014. Reminder: A4 Collision Detection. Due . tonight by midnight. 2. Readings and Homework. Read Chapter 26. “A Heap Implementation” to learn about heaps. Exercise: . Salespeople often make matrices that show all the great features of their product that the competitor’s product lacks. Try this for a heap versus a BST. First, try and . Lecture . 16. CS2110 . Spring 2017. Announcements. Next week’s section: make your . BugTrees. . hashable. .. Watch the tutorial videos on hashing:. http://. www.cs.cornell.edu/courses/cs2110/2017sp/online/hashing/01hashing.html. <number>. Adaptable Priority Queues. 3. a. 5. g. 4. e. © 2014 Goodrich, Tamassia, Goldwasser. Presentation for use with the textbook . Data Structures and Algorithms in Java, 6. th. edition. , by M. T. Goodrich, R. Tamassia, and M. H. Goldwasser, Wiley, 2014. Lecture . 16. CS2110 . Fall 2017. Abstract vs concrete data structures. Abstract data structures are . interfaces. they specify only . interface . (method names and specs). not . implementation. (method bodies, fields, . A binary min-heap allows the operations of push and pop to occur . in an average case of . Q. (1). and . Q. (. ln. (. n. )). time, respectively. Merging two binary min-heaps, however, is an . Q. (. Prof. . Neary. Based on slides from previous iterations of this course. Today’s Topics. Review of Min Heaps. Introduction of Left-. ist. Heaps. Merge Operation. Heap Operations. Review of Heaps. Min Binary Heap. Lecture . 16. CS2110 . Spring 2018. Announcements. A4 due TOMORROW. Late deadline is Sunday.. A5 released. Due next Thursday. .. Deadline for Prelim 1 regrade requests is tomorrow.. Remember to complete your TA evaluations by . QUeues. Today. HW 2 grades went out yesterday. Many of the problems seemed to be a problem with rigor. In proofs, justify what you’re saying and make as much explicit as you can. Today. HW 2 grades went out yesterday. Definition of a . d. -ary min heap . Implementation as a complete tree. Examples of binary, ternary, quaternary, and quinary min heaps. Properties. Relative speeds. Optimal choice is a quaternary heap.